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I'm trying to fit Logistic Regression and SVM on a standardized dataset with two classes - 0 and 1. It is a balanced dataset. When I plot the feature importance, I see that for both Logistic Regression and SVM Regression, one feature(f2) is more important than the other two features. I also notice that correlation between this feature(f2) and y (dependent variable) is higher than that with other. Does correlation affect the result? I mean it should affect, but I need a clear detailed explanation as to how. Correlation is as follows: enter image description here

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The univariate Pearson correlations between y and X variables is often useless. There are many reasons to it such as confounding, nonlinearity etc. It does have some information though but often very limited

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